Abstract
We derive an analytic approximation to the credit loss distribution of large portfolios by letting the number of exposures tend to infinity. Defaults and rating migrations for individual exposures are driven by a factor model in order to capture co-movements in changing credit quality. The limiting credit loss distribution obeys the empirical stylized facts of skewness and heavy tails. We show how portfolio features like the degree of systematic risk, credit quality and term to maturity affect the distributional shape of portfolio credit losses. Using empirical data, it appears that the Basle 8% rule corresponds to quantiles with confidence levels exceeding 98%. The limit law's relevance for credit risk management is investigated further by checking its applicability to portfolios with a finite number of exposures. Relatively hom*ogeneous portfolios of 300 exposures can be well approximated by the limit law. A minimum of 800 exposures is required if portfolios are relatively heterogeneous. Realistic loan portfolios often contain thousands of exposures implying that our analytic approach can be a fast and accurate alternative to the standard Monte-Carlo simulation techniques adopted in much of the literature. © 2001 Elsevier Science B.V.
| Original language | English |
|---|---|
| Pages (from-to) | 1635-1664 |
| Number of pages | 30 |
| Journal | Journal of Banking and Finance |
| Volume | 25 |
| Issue number | 9 |
| DOIs | |
| Publication status | Published - 2001 |
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Lucas, A., Spreij, P. J. C., Straetmans, S. T. M., & Klaassen, P. (2001). An analytical approach to credit risk of large corporate bond and loan portfolios. Journal of Banking and Finance, 25(9), 1635-1664. https://doi.org/10.1016/S0378-4266(00)00147-3
Lucas, A. ; Spreij, P.J.C. ; Straetmans, S.T.M. et al. / An analytical approach to credit risk of large corporate bond and loan portfolios. In: Journal of Banking and Finance. 2001 ; Vol. 25, No. 9. pp. 1635-1664.
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title = "An analytical approach to credit risk of large corporate bond and loan portfolios",
abstract = "We derive an analytic approximation to the credit loss distribution of large portfolios by letting the number of exposures tend to infinity. Defaults and rating migrations for individual exposures are driven by a factor model in order to capture co-movements in changing credit quality. The limiting credit loss distribution obeys the empirical stylized facts of skewness and heavy tails. We show how portfolio features like the degree of systematic risk, credit quality and term to maturity affect the distributional shape of portfolio credit losses. Using empirical data, it appears that the Basle 8% rule corresponds to quantiles with confidence levels exceeding 98%. The limit law's relevance for credit risk management is investigated further by checking its applicability to portfolios with a finite number of exposures. Relatively hom*ogeneous portfolios of 300 exposures can be well approximated by the limit law. A minimum of 800 exposures is required if portfolios are relatively heterogeneous. Realistic loan portfolios often contain thousands of exposures implying that our analytic approach can be a fast and accurate alternative to the standard Monte-Carlo simulation techniques adopted in much of the literature. {\textcopyright} 2001 Elsevier Science B.V.",
author = "A. Lucas and P.J.C. Spreij and S.T.M. Straetmans and P. Klaassen",
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Lucas, A, Spreij, PJC, Straetmans, STM & Klaassen, P 2001, 'An analytical approach to credit risk of large corporate bond and loan portfolios', Journal of Banking and Finance, vol. 25, no. 9, pp. 1635-1664. https://doi.org/10.1016/S0378-4266(00)00147-3
An analytical approach to credit risk of large corporate bond and loan portfolios. / Lucas, A.; Spreij, P.J.C.; Straetmans, S.T.M. et al.
In: Journal of Banking and Finance, Vol. 25, No. 9, 2001, p. 1635-1664.
Research output: Contribution to Journal › Article › Academic
TY - JOUR
T1 - An analytical approach to credit risk of large corporate bond and loan portfolios
AU - Lucas, A.
AU - Spreij, P.J.C.
AU - Straetmans, S.T.M.
AU - Klaassen, P.
PY - 2001
Y1 - 2001
N2 - We derive an analytic approximation to the credit loss distribution of large portfolios by letting the number of exposures tend to infinity. Defaults and rating migrations for individual exposures are driven by a factor model in order to capture co-movements in changing credit quality. The limiting credit loss distribution obeys the empirical stylized facts of skewness and heavy tails. We show how portfolio features like the degree of systematic risk, credit quality and term to maturity affect the distributional shape of portfolio credit losses. Using empirical data, it appears that the Basle 8% rule corresponds to quantiles with confidence levels exceeding 98%. The limit law's relevance for credit risk management is investigated further by checking its applicability to portfolios with a finite number of exposures. Relatively hom*ogeneous portfolios of 300 exposures can be well approximated by the limit law. A minimum of 800 exposures is required if portfolios are relatively heterogeneous. Realistic loan portfolios often contain thousands of exposures implying that our analytic approach can be a fast and accurate alternative to the standard Monte-Carlo simulation techniques adopted in much of the literature. © 2001 Elsevier Science B.V.
AB - We derive an analytic approximation to the credit loss distribution of large portfolios by letting the number of exposures tend to infinity. Defaults and rating migrations for individual exposures are driven by a factor model in order to capture co-movements in changing credit quality. The limiting credit loss distribution obeys the empirical stylized facts of skewness and heavy tails. We show how portfolio features like the degree of systematic risk, credit quality and term to maturity affect the distributional shape of portfolio credit losses. Using empirical data, it appears that the Basle 8% rule corresponds to quantiles with confidence levels exceeding 98%. The limit law's relevance for credit risk management is investigated further by checking its applicability to portfolios with a finite number of exposures. Relatively hom*ogeneous portfolios of 300 exposures can be well approximated by the limit law. A minimum of 800 exposures is required if portfolios are relatively heterogeneous. Realistic loan portfolios often contain thousands of exposures implying that our analytic approach can be a fast and accurate alternative to the standard Monte-Carlo simulation techniques adopted in much of the literature. © 2001 Elsevier Science B.V.
U2 - 10.1016/S0378-4266(00)00147-3
DO - 10.1016/S0378-4266(00)00147-3
M3 - Article
SN - 0378-4266
VL - 25
SP - 1635
EP - 1664
JO - Journal of Banking and Finance
JF - Journal of Banking and Finance
IS - 9
ER -
Lucas A, Spreij PJC, Straetmans STM, Klaassen P. An analytical approach to credit risk of large corporate bond and loan portfolios. Journal of Banking and Finance. 2001;25(9):1635-1664. doi: 10.1016/S0378-4266(00)00147-3
I'm an expert in the field of credit risk management and financial analytics. My depth of knowledge extends to advanced concepts and methodologies used in assessing credit risk for large corporate bond and loan portfolios. To demonstrate my expertise, let's delve into the key concepts mentioned in the provided article.
The article discusses an analytical approach to modeling the credit risk of large portfolios, particularly in the context of corporate bonds and loans. Here are the main concepts highlighted in the abstract:
-
Analytic Approximation to Credit Loss Distribution:
- The authors propose an analytic approximation to model the credit loss distribution of large portfolios.
- This approach involves letting the number of exposures tend to infinity.
-
Factor Model for Defaults and Rating Migrations:
- Individual exposures in the portfolio experience defaults and rating migrations.
- These events are driven by a factor model designed to capture co-movements in changing credit quality.
-
Limiting Credit Loss Distribution:
- The derived credit loss distribution adheres to empirical stylized facts of skewness and heavy tails.
-
Impact of Portfolio Features:
- The article explores how portfolio features such as systematic risk, credit quality, and term to maturity influence the distributional shape of portfolio credit losses.
-
Basle 8% Rule and Confidence Levels:
- Empirical data suggests that the Basle 8% rule corresponds to quantiles with confidence levels exceeding 98%.
-
Relevance to Credit Risk Management:
- The authors investigate the relevance of the limit law for credit risk management.
- Applicability to portfolios with a finite number of exposures is explored.
-
Portfolio Size and hom*ogeneity:
- Relatively hom*ogeneous portfolios of 300 exposures can be well approximated by the limit law.
- A minimum of 800 exposures is required for relatively heterogeneous portfolios.
-
Alternative to Monte-Carlo Simulation:
- The article suggests that the proposed analytic approach can be a fast and accurate alternative to the standard Monte-Carlo simulation techniques widely used in the literature.
The provided citation details the authors (A. Lucas, P.J.C. Spreij, S.T.M. Straetmans, and P. Klaassen) and the publication information for the article in the Journal of Banking and Finance in 2001.
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